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DiveRS 2011 : International ACM RecSys Workshop on Novelty and Diversity in Recommender Systems


When Oct 23, 2011 - Oct 23, 2011
Where Chicago, IL, USA
Submission Deadline Jul 29, 2011
Notification Due Aug 19, 2011
Final Version Due Sep 12, 2011
Categories    recommender systems   diversity   novelty   information retrieval

Call For Papers

* Submission deadline extended: 29 July 2011 *

== News ==

Neil J. Hurley from University College, Dublin, will be our invited speaker with a talk entitled "Towards Diverse Recommendation". More details at

A special issue of ACM Transactions on Intelligent Systems and Technology in the scope of the workshop will be announced after the conference, to which the authors of accepted submissions will be invited to submit an extended version of their paper.

== Scope ==

Most research and development efforts in the Recommender Systems field have been focused on accuracy in predicting and matching user interests. However there is a growing realization that there is more than accuracy to the practical effectiveness and added-value of recommendation. In particular, novelty and diversity have been identified as key dimensions of recommendation utility in real scenarios, and a fundamental research direction to keep making progress in the field. Novelty is indeed essential to recommendation: in many, if not most scenarios, the whole point of recommendation is inherently linked to a notion of discovery, as recommendation makes most sense when it exposes the user to a relevant experience that she would not have found, or thought of by herself –obvious, however accurate recommendations are generally of little use. Not only does a varied recommendation provide in itself for a richer user experience. Given the inherent uncertainty in user interest prediction –since it is based on implicit, incomplete evidence of interests, where the latter are moreover subject to change–, avoiding a too narrow array of choice is generally a good approach to enhance the chances that the user is pleased by at least some recommended item. Sales diversity may enhance businesses as well, leveraging revenues from market niches. It is easy to increase novelty and diversity by giving up accuracy; the challenge is to enhance these aspects while still achieving a fair match of the user's interests. The goal is thus generally to enhance the balance in this trade-off, rather than just a diversity or novelty increase.

DiveRS 2011 aims to gather researchers and practitioners interested in the role of novelty and diversity in recommender systems. The workshop seeks to advance towards a better understanding of what novelty and diversity are, how they can improve the effectiveness of recommendation methods and the utility of their outputs. We aim to identify open problems, relevant research directions, and opportunities for innovation in the recommendation business.

The workshop welcomes the participation of researchers, students, and practitioners in the Recommender Systems community and related areas such as Information Retrieval, Data Mining, Machine Learning, and Human-Computer Interaction, working in different application domains, working on or interested in the workshop topics.

== Topics ==

We invite the submission of papers reporting original research, studies, advances, experiences, or work in progress in the scope of novelty and diversity in Recommender Systems. The topics the workshop seeks to address include –though need not be limited to– the following:

* Modeling novelty and diversity in recommender systems
- Theoretical foundation for novelty and diversity
- Recommendation novelty and diversity models
- Popularity, risk, surprisal, serendipity, freshness, discovery
- Link to diversity models in Information Retrieval
* Novelty and diversity enhancement
- Diversification methods
- Recommendation of long-tail and difficult items, cold-start problem
- Individual vs. global diversity
- Machine Learning for novelty and diversity
* Novelty and diversity across recommendations
- Novelty and diversity in sequential recommendation
- Novelty and diversity in interactive recommendation
- Aggregate diversity
- Novelty and diversity in time and context
- Novelty and trust
* Novelty and diversity evaluation
- Experimental methodologies and design
- Novelty and diversity metrics
- Datasets
- User studies
* Business perspective on novelty and diversity

== Submission ==

Three submission types are accepted: technical papers of up to 8 pages, short technical papers of up to 4 pages, and short position papers up to 4 pages. Each paper will be evaluated by at least two reviewers from the Programme Committee. The papers will be evaluated for their originality, contribution significance, soundness, clarity, and overall quality. Within a required quality standard, position papers will be appreciated for presenting new perspectives and insights, and their potential for provoking thought and stimulating discussion.

All submissions shall adhere to the standard ACM SIG proceedings format: The accepted papers will be published in a specific volume for the workshop in the ACM Proceedings series.

Submissions shall be sent as a pdf file through the online submission system is now open at:

A special issue of ACM Transactions on Intelligent Systems and Technology in the scope of the workshop is in preparation, to which the authors of accepted submissions will be invited to submit an extended version of their paper.

== Important dates ==

Paper submission deadline: 29 July 2011 (extended)
Author notification: 19 August 2011
Camera ready version due: 12 September 2011
DiveRS 2011 workshop: 23 October 2011

== Programme Committee ==

Xavier Amatriain, Telefónica R&D, Spain
Leif Azzopardi, University of Glasgow, UK
Iván Cantador, Universidad Autónoma de Madrid, Spain
Licia Capra, University College London, UK
Òscar Celma, BMAT, Spain
Charles Clarke, University of Waterloo, Canada
Sreenivas Gollapudi, Microsoft Research, USA
Neil Hurley, University College Dublin, Ireland
Oren Kurland, Technion, Israel
Neal Lathia, University College London, UK
Hao Ma, Microsoft Research, USA
Qiaozhu Mei, University of Michigan, USA
Jérôme Picault, Bell Labs, Alcatel-Lucent, France
Filip Radlinski, Microsoft Research, Canada
Davood Rafiei, University of Alberta, Canada
Francesco Ricci, Free University of Bozen-Bolzano, Italy
David Vallet, Universidad Autónoma de Madrid, Spain
Paulo Villegas, Telefónica R&D, Spain
ChengXiang Zhai, University of Illinois at Urbana-Champaign, USA
Tao Zhou, University of Electronic Science and Technology of China, China
Jianhan Zhu, True Knowledge, UK

== Organizers ==

Pablo Castells, Universidad Autónoma de Madrid, Spain
Jun Wang, University College London, UK
Rubén Lara, Telefónica Investigación y Desarrollo, Spain
Dell Zhang, Birkbeck, University of London, UK

Contact email:

More info at:

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